Experimental Evaluation of Cloud-Based Facial Emotion Recognition Services

Authors

  • Ján Magyar Department of Cybernetics and Artificial Intelligence, Technical University of Košice, 042 00 Košice, Slovakia
  • Peter Sinčák Department of Cybernetics and Artificial Intelligence, Technical University of Košice, 042 00 Košice, Slovakia
  • Ivan Čík Department of Cybernetics and Artificial Intelligence, Technical University of Košice, 042 00 Košice, Slovakia
  • Andrinandrasana David Rasamoelina Department of Cybernetics and Artificial Intelligence, Technical University of Košice, 042 00 Košice, Slovakia
  • Cindy L. Bethel Department of Computer Science and Engineering, Mississippi State University, Butler Hall, MS, USA
  • Filippo Cavallo Department of Industrial Engineering, University of Florence, 50139 Firenze, Italy
  • Ammar Hawbani School of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui 230026, China

DOI:

https://doi.org/10.31577/cai_2021_6_1295

Keywords:

Affective computing, cloud computing, facial emotion recognition, Software as a Service

Abstract

The main goal of this paper is to perform an extensive analysis of the accuracy of six selected cloud-based facial emotion recognition services on three facial images datasets. The evaluation was performed on more than 33 000 images depicting eight different emotions. Results show that emotion recognition services show a varying level of accuracy over different types of datasets, having a lower accuracy for images of lower quality, but performing considerably better for images taken in ideal conditions. Based on these results we believe that cloud-based facial emotional recognition services do not have the expected accuracy for some use cases and therefore must be selected with care when developing a system that relies on emotion-based interactions.

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Published

2022-02-18

How to Cite

Magyar, J., Sinčák, P., Čík, I., Rasamoelina, A. D., Bethel, C. L., Cavallo, F., & Hawbani, A. (2022). Experimental Evaluation of Cloud-Based Facial Emotion Recognition Services. Computing and Informatics, 40(6), 1295–1321. https://doi.org/10.31577/cai_2021_6_1295

Issue

Vol. 40 No. 6 (2021): Computing and Informatics

Section

Articles

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